三维人脸表情图像预处理研究

Preprocessing of 3D facial expression image

在三维原始数据的基础上,提出三维人脸表情图像预处理方法.该方法主要进行尖点去除、点云三角化、点云平滑和孔洞修补等有效的预处理工作,并手动提取15个特征点,采用K-NN算法分类实验大大提高三维人脸表情识别率和鲁棒性.

Though the research of 3D facial expression and image is now more and more extensive, the collection of three-dimensional raw data usually contains a lot of redundant information and interference information, which makes computation much larger. These problems will have a negative impact on the extraction of subsequent features, resulting in the extraction of feature points and low accuracy. Therefore,the 3D facial expression image preprocessing methods are put forward based on the raw 3D data. It mainly processes the effective pretreatment work, such as cusp removal, point cloud triangulation, point cloud smoothing and repair work of holes, etc. It manually extracts 15 feature points and uses the K-NN algorithm classification experiments to greatly improve the 3 d facial expression recognition rate and robustness.